Predictive Analytics

Predictive Analytics identifies patterns, structures, and relationships in data and uses this information to make predictions about future events. This involves both classical statistical methods and machine learning techniques.

Predictive Analytics can be distinguished from Descriptive and Prescriptive Analytics. Descriptive Analytics analyzes and describes historical data, identifies patterns, and reveals relationships. Based on this, Predictive Analytics makes statements about the future, generates data-driven forecasts, and assesses the probabilities of potential future events. Prescriptive Analytics translates these future predictions into specific recommendations or identifies the optimal decision.

Predictive Analytics has a wide range of applications.

• Supply Chain – Intelligent supply chain, production, and inventory management: Demand for certain items in a company is forecasted using order history, digital customer information, and current order inputs. Accurate predictions form the basis for optimizing and coordinating raw material purchases, production, and inventory management.
• Smart Grid – The intelligent power grid: The smart grid generates load forecasts and predicts electricity demand. Such load forecasts are becoming increasingly important due to the decentralization of power generation (renewable energies). This is relevant for both the power provider, who must ensure grid stability, and the energy-consuming company, which needs to adapt to the volatile energy market as cost-effectively as possible.
• Predictive Maintenance – Proactive maintenance planning: Intelligent production facilities detect wear and malfunction of machines early using sensor data, allowing maintenance activities to be scheduled on time or coordinated with other planned maintenance tasks.
• Credit Scoring – Probability of loan payment defaults: In credit scoring, banks and companies assess the likelihood that a customer will fail to meet installment payments on a granted loan, enabling them to adjust the terms of the loan accordingly.